With rapid development of information technologies, data is increasing exponentially, and currently has entered an era of massive data. A conventional data storage manner cannot meet a current storage situation. Big data cloudification provides a solution for massive data storage. Currently, a cloud storage technology develops rapidly at home and abroad, and there are some relatively representative storage technologies, such as a HADOOP distributed file system (HDFS) and AMAZON S3. For HDFS storage, in a cluster file system including a computer network and a node, a file fragment is distributed to each node, and data node storage is supported. A client accesses remote storage using a network connection, and if there is a high requirement for read/write operations per second (or input/output operations per second (I/OPS)), performance is relatively poor. AMAZON S3 storage is external storage, a throughput is relatively high, and performance is relatively poor in an application scenario of big data.
In a common method, because each storage technology has a respective storage architecture, data processing is not flexible, and adaptability is relatively poor in different corresponding application scenarios.